In April 1998, the electricity industry in California was deregulated, and the Independent System Operator (ISO) and Power Exchange (PX) were formed to operate the electricity grid and energy/capacity markets. Three sequential spot energy and capacity markets were formed as follows: the PX day-ahead market, the PX day-of market, and the ISO real-time market. In each of the markets, the participants would bid their energy, adjustments for relieving grid congestion, and five types of ancillary services separately, while the ISO and PX would auction these services in their markets correspondingly. This sequential and segregated nature significantly deteriorated the efficiency of the California electricity market, and resulted in a huge cost for California consumers during the 2000-01 energy crisis.
Other deregulated energy markets, such as the PJM ISO (serving Pennsylvania, New Jersey, and Maryland) and NY-ISO (New York ISO), are designed differently and a simultaneous optimal auction is used. In the simultaneous optimal auction, for example, the generators bid their generation into the day-ahead market in terms of energy price curves, start-up cost curves, minimum and maximum generation levels, and physical ramping rates. Hourly energy and ancillary services are procured and paid via the market clearing prices (MCP) for these services respectively, and the total procurement cost is minimized to meet the demand and reserve requirement. A day ahead generation and demand schedule is also produced to satisfy the grid network constraints and individual generation constraints.
Under this mechanism, it is crucial for the ISOs to minimize a proper objective function and to set the MCPs correctly, since market participants are charged or get paid based on the MCPs. The MCPs also have financial impacts on forward transactions outside the ISO markets.
What is lacking in the prior art, however, is a proper objective function to be minimized so that MCPs can be set correctly, and thereby minimize the total procurement cost for consumers. Preferably, the method to minimize this new objective function would use the well-developed formulation and solution methodology of the traditional unit commitment problem.